Do Hard Things (Featuring: Jerry Seinfeld)

The most recent episode of the Acquired podcast featured a story about Jerry Seinfeld that provides a critical lesson for succeeding in our current AI moment. Video from today’s episode: youtube.com/calnewportmedia (0:00) Do hard things (1:30) Technologies and jobs (5:22) AI today (8:19) The solution Links: Buy Cal’s latest book, “Slow Productivity” at www.calnewport.com/slow https://www.youtube.com/watch?v=Wm53dMsn5dk Today’s episode was produced and mastered by Jesse Miller. Nate Mechler provided research and newsletter support. It was edited by Ben Crain and Rob Montz. The theme music is modified from Jay Kerstens. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Cal Newport?

  So I just listened to the most recent episode of the acquired podcast. It focused on the business of Seinfeld. Now, I found the whole thing really fascinating, but there was one story in particular from this episode that really caught my attention. Here, let me play you a clip now.

• 0:18Speaker 01

  The HBR interviewer says, so you cut off the show when it was so successful, really as a result of the fact that you were burned out. Why didn't you try to come up with a more efficient, more sustainable way to make the show? What would McKinsey have said if they'd come in and said, there's a better way to do this? And Jerry says, who's McKinsey? The interviewer says, well, McKinsey's a big consulting firm. Jerry says, are they funny? The interviewer says, no. Jerry says, then I don't need them. The interviewer says, no interest in efficiency. Or Jerry says, no, no. If you're efficient, you're doing it the wrong way. The right way is the hard way.

• 0:57Cal Newport?

  Now, the reason why this caught my attention is that I couldn't shake the thought that this story about comedy writing in the 1990s actually has a lot to tell us about AI and the world of work today. Now, I know that's a bit of an unlikely connection, but I really couldn't shake it. So I thought I would jump on the mic and record a quick episode explaining what I mean. So let's get into it.

• 1:28Cal Newport?

  All right. So how am I going to connect Seinfeld from the 1990s to AI and work today in 2026? To do so, I have to start by introducing a key idea that is central to my thinking and writing about the role of technology in the workplace. And that idea is this. Technologies are not just tools that you deploy as needed to help with various things that you do in your job. Technologies can actually shape the way you think about your job. They can actually change our implicit understanding of what it means to work. Now, I documented this effect, for example, in my 2021 book, here, I'll hold it up here,

• 2:08Cal Newport?

  A World Without Email, which looked deeply at the history of email and how this particular humble tool changed the definition of work. Here's the one minute version of the story. When email first began, it spread through the office. It had a very simple pitch behind it. It was just supposed to replace two existing technologies with a better one, in particular, fax machines and voicemail. So in the late 1980s, right before email began its emergence, look, if you worked in an office, the way you sent information to other offices quickly is you fed sheets of paper into a machine that then sent it over a phone line. And on the other end, another machine printed it back out again. And these were really annoying to use. And then if you wanted to call someone and they weren't there, by the time it got into

• 2:53Cal Newport?

  the 90s, you would use voicemail, which meant you spent a lot of time as an office worker, typing codes into your phone and then listing sequentially through messages that people had left you. The big pitch from email, if you actually go back and read the press coverage in the 80s and 90s, the big pitch was you don't need a fax machine anymore. You don't need voicemail. You can send attachments on email or just send an email to someone and it will sit in their inbox till they check it. No punching in numbers or waiting to hear messages. Right? So it had this very pragmatic pitch. It's just a tool you can use that's better than some other tools you're already using. But when email arrived, the impact was much more substantial than just reducing stress around those existing tools.

• 3:34Cal Newport?

  As email spread, and I document this in my book, it changed for many office workers, it changed how we understood the rhythm of work. Work used to be something that you did as an individual and then would occasionally emerge to collaborate. So we might have a meeting in the conference room midday, but before that meeting, I'm working in isolation and try to move towards outcomes that I can then show you later to justify my worth as an employee. When email came along, work became a sort of implicit virtual back and forth collaboration. It became much more about sending things back and forth as work was unfolding. Hey, what about this? Can you give me this information?

• 4:18Cal Newport?

  Can you take a look at this? So the communication, the conversation itself became a stand-in for work or the thing that we began to focus on more. What it meant to be busy was not like it used to be, hey, look at the reports I wrote this quarter. Those were very good. Or, you know, I'm Don Draper in 1960s Madison Avenue. Look at the ad campaign I finished up this quarter. Kodak loved it. And instead, you became measured more and more implicitly about how involved were you on these ongoing back and forth communications? So the tool changed what work meant. Now, in this case, this change was not a really positive one.

• 4:58Cal Newport?

  Because it turns out that if work really becomes the center on back and forth messaging, you as the worker now has to service inbox all day long because you have to be a part of multiple different back and forth asynchronous communications. Our brain is not good at this because now we're constantly shifting back and forth. We can never settle our focus on any one thing. It's exhausting. It makes us miserable. It makes us stressed out. Eventually, we got Slack, which just codified this idea that we're now in a hyperactive hive mind collaboration. It made it even more hyperactive and it brought in a new age of misery without actually substantially, as far as we can tell in the numbers, increasing the value or quality of things that knowledge work firms were producing. Right? So email is a cautionary tale.

• 5:41Cal Newport?

  New technology is not just a new tool you can choose. It can change your definition of work and maybe towards a definition that is less positive for the people involved. All right, now let's turn to AI now, like in 2020, it's 2026. I would argue that the AI workplace applications being pitched now, especially the idea of agents in the style that computer programmers deploy, these LLM-powered agents are things that all knowledge workers should deploy, is changing the definition of work once again in ways that no one is actually explicitly saying is good. And in particular, I would argue, the new understanding of work that new AI tools are pushing us towards is one that is much more inspired by the assembly line.

• 6:26Cal Newport?

  Except for now, instead of it being an assembly line that produces physical items like cars or washing machines, it's a cognitive assembly line that produces tasks. This is, I'm arguing here, this is the mental model that AI is trying to push us towards, where it says, here's what knowledge work is. It's a bunch of tasks. It's this slide deck gets updated. These numbers get gathered. These bullet points get put into an email that gets sent out to these people. That all of these sort of tasks accumulate to, they add up to the aggregate into this is what work is. Now, why is AI moving us towards that particular understanding of work? Because that's what it can work with. That's what it can improve.

• 7:10Cal Newport?

  It says, yeah, we can now use AI to speed those things up. Well, you can have an AI agent go out and produce the slide deck for you or an LLM help you write that email so you don't have to spend as much time on it. Or have an orchestrator of multiple agents that go out to gather the information to write a draft of a report. And then you can use a chatbot to write an email about the report. And then you could have another agent that sends it out. And so we can speed up the generation and completion of tasks. So just like in the industrial sector, they look to technology to say, we can automate assembly lines. AI says, we can automate cognitive assembly lines.

• 7:50Cal Newport?

  We speed that up, more tasks per day, that feels like productivity. So that's the sort of model of work that AI is pushing us towards. But again, this is a model of work that's not necessarily correct. And we do know, however, that it has negative side effects. When we begin to see ourselves as just cognitive assembly line workers, we just sit there all day long supervising AI agents, sort of executing small value task on our behalf, and we have to supervise and correct and go back. It's kind of a miserable approach to work. It's like being a manager, but without actual human interaction. Your only interaction is with the output of LLM-powered agents and chatbots.

• 8:31Cal Newport?

  Like, it's a pretty miserable definition of work, so we should be wary about it. So what's the solution here? Right? I mean, again, I, this is what I think about technology work. I've written a bunch of books on this. What's the solution to prevent technology from shifting the definition of work in a way that doesn't necessarily make us better, but does make us miserable? The key is you have to have your own understanding of what matters. You have to understand it strongly and believe in it. This is what it means to do my work well. And if you understand that, you're much more immune to a tool showing up and completely changing what you do. This brings us back to Seinfeld. Because what I think Seinfeld was doing in that quote about McKinsey was laying out

• 9:16Cal Newport?

  an alternative way to think about cognitive work, that if you really embrace, will not only produce better results, but give you some immunity to the warping, workplace warping effects of new technologies, whether it's AI today or email yesterday, or whatever new technology is going to come tomorrow. So let's go back and look at the key part of this quote. I'll read it here. If you're efficient, you're doing it the wrong way. The right way is the hard way. So what Seinfeld is saying is that in a lot of cognitive work, the real valuable stuff, the stuff that's actually going to grow your company, going to get you new clients, that's going to make money, the stuff that actually moves the needle, requires this serious application of cognition.

• 10:01Cal Newport?

  You have to think hard. You have to pull together multiple different things you've learned, your human instincts, the creative burst. You need to then, in your mind, iterate through possible configurations, editing them and curate them on the fly to try to figure out which ones seem even better. It's a kind of complicated cognitive dance that if done well with enough attention can produce something that matters, something of real value, whatever the equivalent of a tight Seinfeld script is for your particular line of work. And that is, has nothing to do with efficiency and it's going to be hard. It's going to have a lot of cognitive strain. And Seinfeld's saying, good. Efficiency has nothing to do with this. If you're, you know, I want to produce a good Seinfeld script.

• 10:45Cal Newport?

  I want to produce the ad pitch that Kodak is going to love. I don't care if at the margins I sped certain things up or not. This is going to take me weeks. Fine, it's going to take me weeks. And whether it takes me 21 days or 19 days, doesn't really matter. What matters is, can I do this a few times a year? That produce something that's really valuable?

• 11:04Cal Newport?

  That is a really important model. So if you embrace that model, if that model is applicable to the type of thing you do for a living, you have a lot more defenses against technologies that are coming in and trying to change your definition of work. So like if the email people come along and you're Seinfeld, right? You're trying to write these scripts and the email people come along and say, "You gotta be on this. Look how efficient this is. You can send messages and scripts back and forth, much quicker than using a fax machine or a courier. And if someone needs you, you don't have to check your phone or whatever." Seinfeld will say, "But none of that makes me write the script better. Making that easier doesn't make me write the script better." And in fact, that might make me spend more time communicating with people, none of which helps you write the script better. So I don't care.

• 11:47Cal Newport?

  All right, same thing. You're Seinfeld. Let's use him as our exemplar here. And now you're in 2026 and like AI agents come along saying, "Hey Ben, you should be using these agents, these orchestrators. They could reformat your scripts for you or go help you find jokes and update automatically status spreadsheets of where your script is or whatever." None of that is actually, none of that helps me do the hard work of making the script better. That like being, those things being a little faster doesn't, doesn't actually change the quality of the scripts or my ability to get out 22 scripts a year. That's like at the margins and it might distract me if I have to monitor agents and have all this stuff going on. Then that might take me away from the thing that matters. Now, this doesn't apply to every job, right? There's all sorts of different jobs.

• 12:30Cal Newport?

  And some jobs, you know, are better suited to a hyperactive, high of mind email existence. Other jobs maybe are well suited to an AI agent. Sort of like just want to like orchestrate chatbot interfaces all day, which is terrible, but maybe your job's well suited for that. But I think more cognitive jobs than people realize are essentially Seinfeld in the 1990s. You're trying to, there's some core things you do really well. And you want to do those as well as possible. And the better you do them, the better you do, the better your organization does, the more rewards for everybody. And keeping first things first helps you keep new technologies in your place. You deploy them much more selectively and much more reluctantly. You do not let them change your entire metaphor of work. You do not let them keep you away from the things that matter most.

• 13:14Cal Newport?

  This is the way to navigate the techno marketplace, right? This is the way to navigate technology in the workplace. Know what you're all about and what matters. And if you hold on to that, it doesn't mean that you become nostalgic or like a Luddite exists, you know, resist all technologies, but you deploy them more carefully. You don't deploy them on the cutting edge. If you're on the cutting edge, that means you spend most of your time trying to figure things out. You wait till the cutting edge is past you. You deploy them in ways that are useful. Jerry Seinfeld probably does use email, but he wasn't trying to set up the world's first email servers when he was writing his early Seinfeld scripts. You deploy them more strategically, you deploy technology more reluctantly.

• 13:56Cal Newport?

  You get effect out of it, but the cost to benefit ratio becomes much more advantageous. All right? So that is my connection between Seinfeld and AI. In a lot of work, efficiency is not the goal. We're not on an assembly line trying to, more tasks we produce, the more we can sell to people. That's not how most cognitive jobs work. Hard things, especially cognitive strain, is not something that we try to avoid. In a lot of jobs, that's actually the feeling of producing value. We should try to seek out more hardness. If we don't have enough hardness in our life, that's a problem. And if you know this is the case, you can be much more selective about how you employ technologies. All right? There you go. According to the Seinfeld podcast from Acquired, that show, so Jerry focusing on doing hard stuff and ignoring efficiency,

• 14:40Cal Newport?

  that show has produced somewhere between four to five billion dollars of revenue since its initial conception. So he must be on to something. All right. So that was my thoughts for today. Hope you enjoyed it. Talk to you soon. Today's episode was produced and mastered by Jesse Miller. Nate Meckler provided research and newsletter support. The video was edited by Ben Crain and Rob Moss. The theme music is adapted from an original composition by Jay Kerstens. For weekly ideas from me to show up in your inbox, sign up for my newsletter at calnewport.com.